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Found 7 papers, 1 papers with code
Are Generative AI systems Capable of Supporting Information Needs of Patients?
Given the recent advancements in Generative AI models aimed at improving the healthcare system, our work investigates whether and how generative visual question answering systems can responsibly support patient information needs in the context of radiology imaging data.
Computed Tomography (CT)
Generative Visual Question Answering
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HAiVA: Hybrid AI-assisted Visual Analysis Framework to Study the Effects of Cloud Properties on Climate Patterns
Clouds have a significant impact on the Earth's climate system.
Climate Intervention Analysis using AI Model Guided by Statistical Physics Principles
Our model, AiBEDO, is capable of capturing the complex, multi-timescale effects of radiation perturbations on global and regional surface climate, allowing for a substantial acceleration of the exploration of the impacts of spatially-heterogenous climate forcers.
Accelerating exploration of Marine Cloud Brightening impacts on tipping points Using an AI Implementation of Fluctuation-Dissipation Theorem
Here, we describe an AI model, named AiBEDO, that can be used to rapidly projects climate responses to forcings via a novel application of the Fluctuation-Dissipation Theorem (FDT).
Relationship-aware Multivariate Sampling Strategy for Scientific Simulation Data
With the increasing computational power of current supercomputers, the size of data produced by scientific simulations is rapidly growing.
Deep Learning-Based Feature-Aware Data Modeling for Complex Physics Simulations
Data modeling and reduction for in situ is important.
NNVA: Neural Network Assisted Visual Analysis of Yeast Cell Polarization Simulation
We utilize the trained network to perform interactive parameter sensitivity analysis of the original simulation at multiple levels-of-detail as well as recommend optimal parameter configurations using the activation maximization framework of neural networks.
